RAISEF
Case Study 1: AI-Driven Healthcare Diagnostics
Deployment
Release in a controlled way with approvals, guardrails, and rollback
Enforce privacy and security, publish user disclosures, and connect test evidence to live monitoring.
In Deployment, teams move from verified builds to real users under tight control. Releases follow change approval with staged rollouts, feature flags, and a documented back-out plan. Privacy and security settings are applied exactly as designed, access is least privilege, and logs are tied to identities for audit. User-facing disclosures explain purpose, data use, limits, and support channels. Indicators from testing feed production dashboards so accountability continues after launch, with alerts that trigger human oversight when risk or uncertainty rises. Versioned artifacts, runbooks, and ownership records make it clear who is responsible for operating, pausing, or rolling back the system.
